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1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Holder Codeibi 8JMKD3MGPEW34M/46T9EHH
Identifier8JMKD3MGPAW/3M3PMKS
Repositorysid.inpe.br/sibgrapi/2016/07.11.13.34
Last Update2016:07.11.13.34.27 (UTC) administrator
Metadata Repositorysid.inpe.br/sibgrapi/2016/07.11.13.34.27
Metadata Last Update2022:06.14.00.08.20 (UTC) administrator
DOI10.1109/SIBGRAPI.2016.036
Citation KeyFavarettoDihlMuss:2016:DeCrFe
TitleDetecting crowd features in video sequences
FormatOn-line
Year2016
Access Date2024, May 03
Number of Files1
Size5400 KiB
2. Context
Author1 Favaretto, Rodolfo Migon
2 Dihl, Leandro
3 Musse, Soraia Raupp
Affiliation1 Pontifícia Universidade Católica do Rio Grande do Sul
2 Pontifícia Universidade Católica do Rio Grande do Sul
3 Pontifícia Universidade Católica do Rio Grande do Sul
EditorAliaga, Daniel G.
Davis, Larry S.
Farias, Ricardo C.
Fernandes, Leandro A. F.
Gibson, Stuart J.
Giraldi, Gilson A.
Gois, João Paulo
Maciel, Anderson
Menotti, David
Miranda, Paulo A. V.
Musse, Soraia
Namikawa, Laercio
Pamplona, Mauricio
Papa, João Paulo
Santos, Jefersson dos
Schwartz, William Robson
Thomaz, Carlos E.
e-Mail Addressrodolfo.favaretto@gmail.com
Conference NameConference on Graphics, Patterns and Images, 29 (SIBGRAPI)
Conference LocationSão José dos Campos, SP, Brazil
Date4-7 Oct. 2016
PublisherIEEE Computer Society´s Conference Publishing Services
Publisher CityLos Alamitos
Book TitleProceedings
Tertiary TypeFull Paper
History (UTC)2016-07-11 13:34:27 :: rodolfo.favaretto@gmail.com -> administrator ::
2016-10-05 14:49:10 :: administrator -> rodolfo.favaretto@gmail.com :: 2016
2016-10-13 12:50:18 :: rodolfo.favaretto@gmail.com -> administrator :: 2016
2022-06-14 00:08:20 :: administrator -> :: 2016
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Version Typefinaldraft
Keywordsimage processing
fundamental diagrams
classification
crowd analysis
AbstractWe propose a new methodology to detect social aspects of crowds in video sequences based on pedestrian features, which are obtained through image processing/computer vision techniques. The main idea is to apply and extend the concepts of Fundamental Diagram (FD) with more features, such as grouping and collectivity. Using crowd features we identify the crowd type and the main characteristics. In addition, we also investigated two further results: the visual assessment of people in real video sequences in order to detect crowd characteristics, and the usage of our method to detect similarity of crowds in videos.
Arrangement 1urlib.net > SDLA > Fonds > SIBGRAPI 2016 > Detecting crowd features...
Arrangement 2urlib.net > SDLA > Fonds > Full Index > Detecting crowd features...
doc Directory Contentaccess
source Directory Contentthere are no files
agreement Directory Content
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4. Conditions of access and use
data URLhttp://urlib.net/ibi/8JMKD3MGPAW/3M3PMKS
zipped data URLhttp://urlib.net/zip/8JMKD3MGPAW/3M3PMKS
Languageen
Target FilePID4344647.pdf
User Grouprodolfo.favaretto@gmail.com
Visibilityshown
Update Permissionnot transferred
5. Allied materials
Mirror Repositorysid.inpe.br/banon/2001/03.30.15.38.24
Next Higher Units8JMKD3MGPAW/3M2D4LP
8JMKD3MGPEW34M/4742MCS
Citing Item Listsid.inpe.br/sibgrapi/2016/07.02.23.50 5
Host Collectionsid.inpe.br/banon/2001/03.30.15.38
6. Notes
Empty Fieldsarchivingpolicy archivist area callnumber contenttype copyholder copyright creatorhistory descriptionlevel dissemination edition electronicmailaddress group isbn issn label lineage mark nextedition notes numberofvolumes orcid organization pages parameterlist parentrepositories previousedition previouslowerunit progress project readergroup readpermission resumeid rightsholder schedulinginformation secondarydate secondarykey secondarymark secondarytype serieseditor session shorttitle sponsor subject tertiarymark type url volume


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